Modeling user preferences for effective personalization is one of the central tasks in Web mining. Certain personalization systems seek to provide users with the most relevant information without eliciting their intentions, and relying only on user profiles and their past behavior. Examples of such systems include search personalization, Google News personalization, and Yahoo! behavioral targeting among others.
One application of Web personalization is in recommender systems in e-commerce sites such as Amazon, Netflix, or eBay, which attempt to recommend relevant items to users based on their explicit profiles (e.g., gender and age) and their implicit profiles, such as purchasing and browsing behavior. The combined user profiles are then used to suggest items deemed as the most relevant items.